Evaluation of Agronomic and Seed Characteristics in Elevated Oleic Acid Soybean Lines in the South-Eastern US

Increasing oleic acid, a monounsaturated fatty acid, is reported to strike the best balance between cold flow properties and oxidative stability in soybean seed oil to enhance biodiesel and produce a better burning fuel. In addition, it is important that elevated oleic acid soybeans have the agronomic traits of local cultivars and maintain oleic acid stability across environments. Research was conducted in 2007–2008 to evaluate six Roundup Ready^® soybean recombinant inbred lines exhibiting enhanced levels of oleic acid. The six elevated oleic lines averaged a 55% increase in oleic acid and a 43% decrease in linolenic acid over the two commercial cultivars (AG3906 and AG4103). Some elevated oleic acid genotypes fulfilled the linear regression definition of a stable genotype. TN03-93RR was the best genotype because of its oleic acid content (397 g kg^?1) and desirable regression estimates for stability. Iodine value (IV), peroxide value (PV), and induction period (IP) were used to evaluate the fuel properties of the two lines with the highest oleic acid content and the two commercial cultivars. The elevated oleic acid lines had significantly better IP, PV and IV for better biodiesel properties and oxidative stability than the two commercial cultivars.     

Improving database performance with a mixed fragmentation design

The performance of database operations can be enhanced with an efficient storage structure design using attribute partitioning and/or tuple clustering. Previous research deals mostly with attribute partitioning. We address here the combined problem of attribute partitioning and tuple clustering. We propose a novel approach for this mixed fragmentation problem by applying a genetic algorithm iteratively to attribute partitioning and tuple clustering sub-problems. We compared our results to attribute-only partitioning and random search solution, resulting in a database access cost reduction of upto 70% and 67% respectively. We analyzed the effect of varying genetic parameters on the optimal solution through experimentation.     

Molecular structure and driving force to metastable states: Janus faces in polymer crystallization

This paper is a retrospective of a past dedicated to research on polymers and a situation sketch of the present and the near future. (Co)polymers discussed are mainly based on ethylene. (Cross‐)fractionation techniques combined with state‐of‐the‐art characterization techniques, like quantitative differential scanning calorimetry, are powerful tools for the study of the links between two main topics: molecular structure and crystallization/melting. These form the two ‘Janus faces’ polymers can show, namely Face 1: the molecular structure resulting from polymerization with the keyword ‘nature’; and Face 2: the driving force of crystallization towards a metastable state, with the keyword ‘nurture’. After all, to meet demands for properties of products, in principle one starts with a given molecular architecture, after which dedicated processing, including application of temperature–time ramps, has to do the job. With new instrumentation, especially fast scanning (chip) calorimetry, for the first time in history the driving force towards crystallization into one of the possible metastable states – via Face 2 – can be controlled, of course within certain limits given by Face 1. This promising outlook of combining the faces to a useful symbiosis of Janus will be a challenge for those working in the science of crystallization of polymers. © 2018 Society of Chemical Industry     

Status of ITER dimensional tolerance studies

The optimization of the manufacturing/assembly tolerances and processes in ITER Experimental Nuclear Fusion Device is one of the key tasks to optimize the fabrication cost, to prevent problems during assembly and to ensure that the critical homogeneity of the magnetic field and the positioning requirements of the plasma facing components can be achieved. This task is further complicated by the strong interplay among the various Tokamak systems, as for instance in the inner region of the machine where the clearances between Central Solenoid, Toroidal Field Coils, Thermal Shield, Vacuum Vessel and In-Vessel components have been minimized for their large influence on the magnetic flux and the overall machine cost.A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. The dimensional variation model is representative of Tokamak functional tolerances and processes, predicting accurate values for the amount of variation on critical areas. In addition, dimensional simulations help to determine the key tolerances that contribute to a particular variation.This paper describes the current status of the Tokamak dimensional variation studies and its management plan, highlighting the status of compliance of allocated tolerances with input requirements. Management of risk issues and corrective actions are also described.     

Fault diagnosis based on adaptive observer for a class of non-linear systems with unknown parameters

In this paper, the fault diagnosis problem for a class of non-linear systems with uncertainty which depends on states, inputs and unknown constant parameters is discussed. Under some geometric conditions, the system is transformed into two different subsystems. One is not affected by actuator faults, so a non-linear adaptive observer can be designed based on the assumption of the strictly positive realness (SPR). The other whose states can be measured is affected by the faults. Actuator fault diagnosis is based on estimations of both the state and the unknown parameters with good accuracy. Discussions on release of SPR requirement and extension to the sensor fault case are also made. Finally, two examples are given in order to illustrate the applicability of the proposed methods for actuator fault diagnosis and sensor fault diagnosis respectively.     

Method to characterize the fire behavior of materials assemblies

The fire behavior of various large samples polymers assemblies is an under‐researched topic. In fire risk assessment, the resultant heat release rate of burning different combustibles has to be known. To highlight interactions between components, 2 types of configurations were tested: juxtaposed and layered materials, using a specific radiant panel setup. For juxtaposed assemblies, results indicated that the more flammable component acted as an accelerator for the global combustion kinetics. For layered assemblies, 2 main phenomena were evidenced: the front material acted as a shield delaying the combustion of the backside material and the presence of a backside material induced a thermal thickening that slowed down the combustion of the front material. The experimental burning behaviors of the assembly were compared with a simulated one calculated from the superposition principle. This method was described by introducing a time offset and/or a slowdown factor in the model, confirmed with the use of different assemblies.     

Contactless Spin Switch Sensing by Chemo-Electric Gating of Graphene

Direct electrical probing of molecular materials is often impaired by their insulating nature. Here, graphene is interfaced with single crystals of a molecular spin crossover complex, [Fe(bapbpy)(NCS)₂], to electrically detect phase transitions in the molecular crystal through the variation of graphene resistance. Contactless sensing is achieved by separating the crystal from graphene with an insulating polymer spacer. Next to mechanical effects, which influence the conductivity of the graphene sheet but can be minimized by using a thicker spacer, a Dirac point shift in graphene is observed experimentally upon spin crossover. As confirmed by computational modeling, this Dirac point shift is due to the phase-dependent electrostatic potential generated by the crystal inside the graphene sheet. This effect, named as chemo-electric gating, suggests that molecular materials may serve as substrates for designing graphene-based electronic devices. Chemo-electric gating, thus, opens up new possibilities to electrically probe chemical and physical processes in molecular materials in a contactless fashion, from a large distance, which can enhance their use in technological applications, for example, as sensors.     

Lithium-Ion Desolvation Induced by Nitrate Additives Reveals New Insights into High Performance Lithium Batteries

Electrolyte additives have been widely used to address critical issues in current metal (ion) battery technologies. While their functions as solid electrolyte interface forming agents are reasonably well-understood, their interactions in the liquid electrolyte environment remain rather elusive. This lack of knowledge represents a significant bottleneck that hinders the development of improved electrolyte systems. Here, the key role of additives in promoting cation (e.g., Li⁺) desolvation is unraveled. In particular, nitrate anions (NO₃⁻) are found to incorporate into the solvation shells, change the local environment of cations (e.g., Li⁺) as well as their coordination in the electrolytes. The combination of these effects leads to effective Li⁺ desolvation and enhanced battery performance. Remarkably, the inexpensive NaNO₃ can successfully substitute the widely used LiNO₃ offering superior long-term stability of Li⁺ (de-)intercalation at the graphite anode and suppressed polysulfide shuttle effect at the sulfur cathode, while enhancing the performance of lithium–sulfur full batteries (initial capacity of 1153 mAh g⁻¹ at 0.25C) with Coulombic efficiency of ≈100% over 300 cycles. This work provides important new insights into the unexplored effects of additives and paves the way to developing improved electrolytes for electrochemical energy storage applications.